tz-hmc opened a new issue #8591: How do I make a siamese network with pretrained models (esp. keeping the weights the same?) URL: https://github.com/apache/incubator-mxnet/issues/8591 ## Description How do I ensure the weights are kept the same? Can I unpack the internal layers somehow and set the weights of each to the same variable? My apologies, I'm new to MXNet. Would really appreciate the help, thanks! `` sym1, arg_params1, aux_params1 = mx.model.load_checkpoint('resnet-152', 0) sym2, arg_params2, aux_params2 = mx.model.load_checkpoint('resnet-152', 0) layer1 = sym1.get_internals() layer2 = sym2.get_internals() for i in range(len(layer1)): # will something like this work? arg_params1[i] = arg_params2[i] `` Relevant answers, but not specific enough to my particular problem: https://github.com/apache/incubator-mxnet/issues/772 siamese networks https://github.com/apache/incubator-mxnet/issues/6791 extract layers as variables https://github.com/apache/incubator-mxnet/issues/557 set weights to be same
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